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Author: Loiane GronerPublisher: Packt Publishing LtdISBN: 1788624947Format: PDF, ePub, DocsDownload Now
Create classic data structures and algorithms such as depth-first search and breadth-first search, learn recursion, as well as create and use a heap data structure using JavaScript Key Features Implement common data structures and the associated algorithms along with the context in which they are used Master existing JavaScript data structures such as arrays, sets, and maps, and learn how to implement new ones such as stacks, linked lists, trees, and graphs in ES 8 Develop abstract data types to make JavaScript a more flexible and powerful programming language Book Description A data structure is a particular way of organizing data in a computer to utilize resources efficiently. Data structures and algorithms are the base of every solution to any programming problem. With this book, you will learn to write complex and powerful code using the latest ES 2017 features. Learning JavaScript Data Structures and Algorithms begins by covering the basics of JavaScript and introduces you to ECMAScript 2017, before gradually moving on to the most important data structures such as arrays, queues, stacks, and linked lists. You will gain in-depth knowledge of how hash tables and set data structures function as well as how trees and hash maps can be used to search files in an HD or represent a database. This book serves as a route to take you deeper into JavaScript. You’ll also get a greater understanding of why and how graphs, one of the most complex data structures, are largely used in GPS navigation systems in social networks. Toward the end of the book, you’ll discover how all the theories presented in this book can be applied to solve real-world problems while working on your own computer networks and Facebook searches. What you will learn Declare, initialize, add, and remove items from arrays, stacks, and queues Create and use linked lists, doubly linked lists, and circular linked lists Store unique elements with hash tables, dictionaries, and sets Explore the use of binary trees and binary search trees Sort data structures using algorithms such as bubble sort, selection sort, insertion sort, merge sort, and quick sort Search elements in data structures using sequential sort and binary search Who this book is for If you’re a JavaScript developer who wants to dive deep into JavaScript and write complex programs using JavaScript data structures and algorithms, this book is for you.

Author: Douglas BaldwinPublisher: Cengage LearningISBN: 1584502509Format: PDF, ePub, DocsDownload Now
While many computer science textbooks are confined to teaching programming code and languages, Algorithms and Data Structures: The Science of Computing takes a step back to introduce and explore algorithms -- the content of the code. Focusing on three core topics: design (the architecture of algorithms), theory (mathematical modeling and analysis), and the scientific method (experimental confirmation of theoretical results), the book helps students see that computer science is about problem solving, not simply the memorization and recitation of languages. Unlike many other texts, the methods of inquiry are explained in an integrated manner so students can see explicitly how they interact. Recursion and object oriented programming are emphasized as the main control structure and abstraction mechanism, respectively, in algorithm design. Designed for the CS2 course, the book includes text exercises and has laboratory exercises at the supplemental Web site. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

Author: Bruno R. PreissPublisher: John Wiley & SonsISBN: 9788126516438Format: PDF, ePubDownload Now
About The Book: Bruno Preiss presents readers with a modern, object-oriented perspective for looking at data structures and algorithms, clearly showing how to use polymorphism and inheritance, and including fragments from working and tested programs. The book uses a single class hierarchy as a framework to present all of the data structures. This framework clearly shows the relationships between data structures and illustrates how polymorphism and inheritance can be used effectively.

Author: J.A. StorerPublisher: Springer Science & Business MediaISBN: 146120075XFormat: PDF, ePub, MobiDownload Now
Data structures and algorithms are presented at the college level in a highly accessible format that presents material with one-page displays in a way that will appeal to both teachers and students. The thirteen chapters cover: Models of Computation, Lists, Induction and Recursion, Trees, Algorithm Design, Hashing, Heaps, Balanced Trees, Sets Over a Small Universe, Graphs, Strings, Discrete Fourier Transform, Parallel Computation. Key features: Complicated concepts are expressed clearly in a single page with minimal notation and without the "clutter" of the syntax of a particular programming language; algorithms are presented with self-explanatory "pseudo-code." * Chapters 1-4 focus on elementary concepts, the exposition unfolding at a slower pace. Sample exercises with solutions are provided. Sections that may be skipped for an introductory course are starred. Requires only some basic mathematics background and some computer programming experience. * Chapters 5-13 progress at a faster pace. The material is suitable for undergraduates or first-year graduates who need only review Chapters 1 -4. * This book may be used for a one-semester introductory course (based on Chapters 1-4 and portions of the chapters on algorithm design, hashing, and graph algorithms) and for a one-semester advanced course that starts at Chapter 5. A year-long course may be based on the entire book. * Sorting, often perceived as rather technical, is not treated as a separate chapter, but is used in many examples (including bubble sort, merge sort, tree sort, heap sort, quick sort, and several parallel algorithms). Also, lower bounds on sorting by comparisons are included with the presentation of heaps in the context of lower bounds for comparison-based structures. * Chapter 13 on parallel models of computation is something of a mini-book itself, and a good way to end a course. Although it is not clear what parallel

Author: Bradley N. MillerPublisher: Franklin Beedle & AssocISBN: 9781590282571Format: PDF, MobiDownload Now
THIS TEXTBOOK is about computer science. It is also about Python. However, there is much more. The study of algorithms and data structures is central to understanding what computer science is all about. Learning computer science is not unlike learning any other type of difficult subject matter. The only way to be successful is through deliberate and incremental exposure to the fundamental ideas. A beginning computer scientist needs practice so that there is a thorough understanding before continuing on to the more complex parts of the curriculum. In addition, a beginner needs to be given the opportunity to be successful and gain confidence. This textbook is designed to serve as a text for a first course on data structures and algorithms, typically taught as the second course in the computer science curriculum. Even though the second course is considered more advanced than the first course, this book assumes you are beginners at this level. You may still be struggling with some of the basic ideas and skills from a first computer science course and yet be ready to further explore the discipline and continue to practice problem solving. We cover abstract data types and data structures, writing algorithms, and solving problems. We look at a number of data structures and solve classic problems that arise. The tools and techniques that you learn here will be applied over and over as you continue your study of computer science.

Author: Michael T. GoodrichPublisher: John Wiley & SonsISBN: 1118771338Format: PDFDownload Now
The design and analysis of efficient data structures has long been recognized as a key component of the Computer Science curriculum. Goodrich, Tomassia and Goldwasser's approach to this classic topic is based on the object-oriented paradigm as the framework of choice for the design of data structures. For each ADT presented in the text, the authors provide an associated Java interface. Concrete data structures realizing the ADTs are provided as Java classes implementing the interfaces. The Java code implementing fundamental data structures in this book is organized in a single Java package, net.datastructures. This package forms a coherent library of data structures and algorithms in Java specifically designed for educational purposes in a way that is complimentary with the Java Collections Framework.

Author: Charles F. BowmanPublisher: Oxford University Press, USAISBN: 0195174801Format: PDF, ePub, DocsDownload Now
With numerous practical, real-world algorithms presented in the C programming language, Bowman's Algorithms and Data Structures: An Approach in C is the algorithms text for courses that take a modern approach. For the one- or two-semester undergraduate course in data structures, it instructs students on the science of developing and analyzing algorithms. Bowman focuses on both the theoretical and practical aspects of algorithm development. He discusses problem-solving techniques and introduces the concepts of data abstraction and algorithm efficiency. More importantly, the text does not present algorithms in a "shopping-list" format. Rather it provides actual insight into the design process itself.